Private transfers and public policy in developing countries : a case study for Peru

Policy, Planning, and Research WORKING PAPERS Public Economics Country Economics Department The World Bank December 1989 WPS 345 Private Transfers and Public Policy in Developing Countries A Case Study for Peru Donald Cox and Emmanuel Jimenez Private transfers within households are affected by such public subsidy programs as social security and health coverage. It is important to monitor this relationship since the impact of these programs, as well as who benefits from them, are also affected. The Polizy, Planning, and Research Complex distnbutes PPR Working Papers to disseninate the findings of work in progress and to encourage the exchange of ideas among Bank staff and aU others interested in development issues. These papers carry the names of the authors, reflect only their views. and should be used and cited accordingly. The findings, interpretations. and conclusions arm the authors' own. They should not be attributed to theWorld Bank, its Board of Directors, its management, or arny of its member countries.  Plc,Planning, and Research | Public Eoonomics Private interhousehold cash transfers are an These transfers are important to consider important source of income in many developing when making policy that is directed toward countries. Cox and Jimenez' review of the certain groups. Increased public spending on, lieterature indicates that the percentage of say, pensions or health benefits, could lower households receiving private transfers in a private spending. For example, altruistically sample of five developing countries ranges from minded middle-aged households may not givc as 19 to 47 percent. The amounts transferred are much to their elderly parents if they know that not trivial - they constitute from 2 to 20 the state would take care of them. The program percent of income among all households, and 10 could have the unintended effect of transferring to 46 percent of income among recipient house- purchasing power to the private donor. Also, the holds. value of the public program's benefits accruing to intended beneficiaries would be lower than Although precise transfer patterns are only the amount of the public transfer. Cox and beginning to be researched, Cox and Jimenez Jimenez provide a conceptual framework to review the preliminary evidence from other show that these displacement effects become studies and conduct original analysis based on less important if households are also motivated the recent Peru Living Standards Survey. The by the expectation that they will get something paper reveals that private transfers are being in exchange, rather than by pure altruism. directed toward vulnerable groups in society. The poor. the elderly, the very young, the Although such private adjustments do offset disabled, the unemployed, and female-headed the impact of public programs, the empirical households all receive disproportionately more evidence indicates that it would not completely transfers than their share in the population. The eliminate them. For example, in Peru, Cox and results can be dramatic and can do more for the Jimenez estimate the amount that private trans- poor than public transfer programs. For cx- fers from young to old would be raised if social ample, in Peru, the lowest income quintile's security payments were eliminated. The an- sh.are in total income is increased by 14 percent swer? Private transfers would rise by about 20 as a result of private transfers. In contrast, percent, but would not completely compensate public transfers (mostly social security pay- for the elimination of social security payments. ments) increase that quintile's income share by The displacement effect of private transfers is only 4 percent. less than that predicted by the purely altruistic model. This paper is a product of the Public Economics Division, Country Economics De- partment. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Ann Bhalla, room N10-059, extension 60359 (98 pages with figures and tables). The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Planning, and Researchi Complex. An objective of the series is to get these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank. Produced at the PPR Dissemination Center  - 1.- OUTLINE I. INTRODUCTION AND SUMMARY ............................................. 1 II. SOCIAL OBJECTIVES THROUGH PRIVATE TRANSFERS: A REVIEW .... ........... 5 A. The Size of Private Transfers .................................... 5 B. Why Private Transfers Are Important .............................. 7 C. Motives for Private Transfers .................................... 8 D. Empirical Evidence on Private Transfers .......................... 12 1. Transfers and Inequality ..................................... 12 2. Transfers as Social Insurance ................................ 14 3. Migration and Education ......................................6 16 E. Public Policy and Private Transfers .............................. 17 F. Conclusions ...................................................... 18 III. WHO GIVES AND WHO GETS PRIVATE INTER-HOUSEHOLD TRANSFERS IN PERU? ....20 A. Data ........................................................ 21 B. Transfers and the Distribution of Welfare ........................ 23 C. Transfers as Social Insurance .................................... 29 D. Transfers, Rural/Urban Differences and Migration ................. 35 E. Public and Private Transfers ..................................... 38 F. Conclusions ....... . ............................................. 40 IV. MOTIVES FOR PRIVATE INTERGENERATIONAL TRANSFERS: AN ANALYTICAL FRAMEWORK AND PRELIMINARY EVIDENCE FROM PERU ......................... 41 A. Theory ........................................................... 42 1. Altruism ..................................................... 43 2. Exchange Through Inter-generational Loans .................... 46 3. Transfers Amounts and Altruism Versus Exchange ............... 49 C. Data ............................................................. 51 D. Empirical Estimates .............................................. 55 1. Estimating Forms ............................................. 55 2. Results: Who Receives Transfers and How Much? ............... 57 3. Results: Who Gives Transfers and How Much? .................. 64 E. Conclusions ...................................................... 69 V. THE CONNECTION BETWEEN SOCIAL SECURITY AND PRIVATE TRANSFERS IN PERU .71 A. Theories of Private Transfers .................................... 73 1. Altruism ..................................................... 73 2. Self-Interest ................................................ 74 3. Altruism and Self-Interest ................................... 76  - il - B. The Social Security System in Peru ............................... 77 C. Data . .79 D. Empirical Estimates .82 1. Estimating Equations ....................... 82 2. Results .84 E. Effects of Social Security on Transfers from Young to Old .. 87 1. Simulation Results .89 2. Implications for Transfer Motives .90 F. Social Security Health Coverage and ;'rivate Transfers .92 G. Conclusions ...................................................... 94 REFERENCES ...................................... 96 The work on this paper was supported in part by RPO 674-49 of the World Bank's Research Support Budget. We wish to thank the Government of Peru and the Bank's Living Standard Measurement Study (LSMS) team for providing us with access to data. i3rge Castillo, Kalpana Mehra, and Reza Firuzabadi were invaluable in setcing up workable data files. Fiona Mackintosh edited the papers in this project. We also acknowledge comments from Bela Balassa and participants at a seminar sponsored by the World Bank's Public Economics Division.  - iii - List of Tables Table 2.1. Private Transfers in Selected Countries ........................ 6 Table 3.1. Effects of Public and Private Transfers on the Distribution of Well-Being .................................................. 26 Table 4.1. Selected Characteristics of Urban Households by Private Transfers Status ............................................... 53 Table 4.2. Probit and Generalized Tobit Estimates Transfers Received ...... 58 Table 4.3. Probit and Generalized Tobit Estimates Transfers Given ......... 65 Table .1. Probit and Generalized Tobit Estimates Transfers from Young to Old Transfers Received ...................................... 85 Table 5.2. Probit and Generalized Tobit Estimates Transfers from Young to Old Transfers Given ......................................... 88 Table 5.3. Probit and Generalized Tobit Estimates Entire Sample Transfers Received ............................................. 93 List of Fijures Figure 3.1 Sources of Transfers in Peru (Percent) ......................... 24 Figure 3.2a Percentage of Households Receiving Transfers by Education of Household Heads ............................................. 28 Fi#ure 3.2b Average Amount of Transfers Received by Education of Household Head ................................................. 28 Figure 3.3a Percentage of Households Receiving Transfers by Age of Household Head ................................................. 31 Fizure 3.3b Average Amount of Transfers Received by Age of Household Head ........................................................... 31 Figure 3.4a Sources and Destination of Private Transfers in Peru ........... 37 Figure 3.4b Percentage of Intis Transferred by Geographic Location ......... 37 Figgre 4.1 Probability of Transfer Receipts Over the Life Cycle ........... 60 Figure 4.2 Log-Compensation--Age Profile .................................. 60 Figure 4.3 Probability of Giving a Transfer Over the Life Cycle ........... 68  I. INTRODUCTION AND SUMHARY Private inter-household transfers are an important component of household income and expenditures in nearly all developing countries. These transfers serve a variety of social and economic functions, including insurance against income shortfalls, support for the elderly in retirement, educational loans, help during illness and the funds for rural-urban migration. Private transfers help overcome imperfections in capital markets. Some transfers are business loans (or repayments). Thus, a significant amount of redistribution may occur within the private sector. Prlicymakers should pay attention to the connection between private and public transfers. Private transfers can affect the formulation of appropriate public policy for a number of reasons. First, private transfets can mitigate or amplify the effect of public expenditures. Depending upon the motive for giving, increased public spending on, say, pensions or health could lower private spending. For example, a public ptvgram for old-age support might reduce incentives for younger households to help their elderly parents. The program could have the unintended effect of transferring income indirectly to the young by easing the burden of provlding for their parents. Also, the measured impact on recipient welfare would be less than that predicted had there been no private transfer response to the program. Second, public revenue mobilization, such as income taxation may, perhaps unintentionally, affect private giving. Third, government regulation of financial intermediaries may restriet access to formal credit market to such an extent that inter- household transfers take up the slack. Fourth, private transfers may facilitate labor mobility and household migration.  - 2 - Up to now, there has been little policy-oriented research on this issue, primarily because the scarcity of survey data. Researchers have only recently begun to study private transfers using newly available survey micro-data sets. Empirical work is in its early stages, and researchers are finally beginning to analyze motivations for private-transfer behavior. Our research, partly stimulated by the Bank's special initiatives on poverty and on private sector development, explores the magnitude and determinants of private transfers in developing countries. This paper reviews work done outside the Bank and contributes to that literature with an analysis of private transfers using the Peruvian Living Standard Survey (PLSS), but many findings are relevant for other developing countries as well. The PLSS is particularly appropriate for the analysis because it contains detailed information on income, remittances, consumption, and the use of public services. The rest of this paper presents four essays (Chapters 2-5) on the topic. Chapter 2 surveys existing literature on private transfers patterns and magnitudes. It finds that private inter-household transfers are an important component of household income and expenditures in many developing countries. For example, case studies in El Salvador, Indonesia, Kenya, and Peru report that about 30 to 50 percent of all households receive transfers. The amounts transferred are also significant. Transfers can be up to 20 to 40 percent of recipient income in many cases. Though inter- country comparisons are difficult, due to disposition ^ transfers definitions and sample coverage, the bulk of survey evidence indicates that private transfers in developing countries are important in terms of both incidence and amount.  Chapter 3 describes private transfer patterns in Peru using the PLSS data. Private transfers flow from high to low.-income households, narrowing income inequality. They follow a pronounced life-cycle pattern, and are targeted toward aged and young hi oeholds. Households in their prime earning years (mid-forties) are a large source of transfers. Transfers are also targeted toward households affected by illness and unemployment and to female-headed households. Many, but not all, transfers cross urban-rural boundaries. These patterns tend to be similar to those f'-k,d in other developing countries. Chapter 4 develops a theoretical framework for analyzing motives for private transfers and provides empirical evidence on transfer motives. A priori, there are at least two possible motives for private transfers. Households might give, with no strings attached, simply because they came about the well-being of members of other households (altruism). Alternatively, households might transfer income in return for some in-kind quid pro quo on future monetary repayment (exchange). The motive for private transfers will affect the impact of public income redistribution. Altruistically-motivated transfers can offset or completely neutralize the impact of public transfers. The reason is that altruistically-linked spending units (such as a child and parent or a husband and wife) act almost as one consumer would. Changes in incomes of individuals due to, say, a change in public subsidies, would not affect consumption of individual members as long as aggregate income of the altruistically-lii d spending unit remained the same. But exchange-motivated transfers interact with public policy much differently, and can even amplify the effects of public transfers. The evidence from Peru does not support the altruism model. Thus, the effect of public transfer programs is not neutral.  -4- Chapter 5 investigates the link between private transfers and one important public program -- social security. Although the offset may not be complete, private transfers still may mitigate the effect of public transfers. But by how much? The theoretical framework is used for an empirical study of the link between one public program -- social security -- and privatKa transfers in Pe.u. Private transfers from young to old would have been twenty percent higher without social security. Also, health coverage from social security reduces private transfers targeted to households affected by illness. However significant, the displacement of private transfers is less than that predicted by models with alruistic motives. The paper also suggests some directions for future research. This study can be easily replicated for other similar data bases (such as in those countries that are the subject of living standards measurement surveys). Moreover, the scope of the work can be broadened to include the impact of other public subsidies (e.g., education) on private transfers. Also, more work can be undertaken to measure non-monetary private transfers. Finally, the studies focus only on interhousehold transfers. Individual-level data would be required to see what happens intra- household.  -5- II. SOCIAL OBJECTIVES THQROUH PRIVATE TRANSFERS: A REVIEW This chapter reviews the literature about private transfers with a focus on developing countries. lie address the following qt' stions. How large are public transfers? Why do they occur? What are the empirical patterns of private transfers? Can we anticipate how they will react to public policy? A. The Size of Private Transfer] Table 1 provides a listing of private-transfer information for an assortment of countries. We constructed it from a variety of sources, so transfer definitions are not strictly comparable. But the table points out the importance of private transfers in many countries. For example, among a sample of urban poor in El Salvador, 33 percent reported receiving private transfers, and private transfer income accounted for 38 percent of total income among recipients. Ninety-three percent of a rural south- Indian sample received transfers from other households. ~n Malaysia, private transfers accounted for almost one-half the income of low-income households. Nearly three-quarters of rural households in Java in Indonesia gave private transfers to other households. And about half of a sample of Filipino households received private cash transfers. Rempel and Lobdell (1978) surveyed economic and anthropological studies of urban-to-rural remittances covering countries in Asia, Africa and Latin America, and found significant private transfers in virtually all instances. Remittances accounted for significant fractions of income in Tanzania, Nigeria, Ghana, Liberia and Pakistan. Further, private transfers are not strictly a reflection of rural-urban migration. Knowles and Anker (1981), for example, found that over half of all transfers for a sample of Kenyan households did not cross urban-rural boundaries.  -6- Table 2.1. Private Transfezs in Selected Countries Average Transfer Amount Year Per capit-a GNP Percent HH's (as percent of income) Country Dollars (1986) Receiving Giving Receiving Giving El Salvador a/ 1976 820 Urban poor 33 -- 11,38 1/ -- India b/ 1975-83 290 Rural households 93 -- 8 -- Indonesia (Java) c/ 1982 490 Rural 31 72 10 8 Urban 44 45 20 3 Kenya 300 Urban d/ 1968 -- 59 -- 3,21 1/ Nairobi e/ 1971 -- 89 -- 21 Nationwide f/ 1974 -- 27 3 4 Rural -- 19 2 3 Urban -- 62 4 6 Malaysia g/ 1977-78 1,830 19/30 m/ 33/47 m/ 11-46 n/ -- Mexico h/ 1982 1,860 Two villages -- -- -- 16/21 -- Peru i/ 1985 1,090 22 23 2,9 1/ 1,6 1/ Philippines j/ 1978 560 47 -- 9 -- USA k/ 1979 17,480 15 -- 1,6 -- a/ Kaufmann and Lindauer (1986). b/ Behrman and Deolalikar (1987). c/ Ravallion and Dearden (1988). d/ Sample of recent migrants, Rempel and Lobdell (1978). e/ Sample of poor households, Johnson and Whitelaw (1974). f/ Knowles and Anker (1981). g/ Butz and Stan (1982). h/ Stark, Taylor and Yitzhaki (1988). i/ Chapter 3, below, in this paper. Average transfer amount computed as proportion of total consumption. j/ Kaufmann (1982). Cash gifts in a large informal housing area. k/ Cox (1987). Additional information available in Cox and Raines (1985). 1/ Number after comma denotes amounts among sample of recipients/givers only. m/ Numbers before and after slash denote upper and lower bounds. n/ Second number denotes proportion for households in .om;est income quintile.  - 7 - B. WhX Private Transfers Akre-Ipomtwt The evidence in table 1 actests to the magnitude of private transfers, but size or frequency is not sufficient reason to pay attention to them. Transfers are only partly determined by custom. Private tran;tfers also respond to social, economic and policy factors. As such they could affect public policy oue-omes in ur.expectud ways. Consider a hypothetical case of two related households, one young and one old, who pool and share the. resources, so that the consumption of individual members is based on aggregate income of the two. Introducing a social security program that taxes the younger household and subsidizes the older one, but leaves aggregated income unchanged, may leave the consumption of the individual household members unchanged as well. The policy might have no effect on the distribution of well-being. Further, if the program involves administrative costs, both households could be made worse off. Consioer a related problem -- evaluating the effectiveness of public health insurance on the distribution of well-being. A simple approach is to subtract appropriately valued health benefits from household income and compare income distributions before and after the substraction. But if the program were really removed private inter-household transfers might fill the gap. A pervasive network of private safety nets could offset changes in public transfers. Put another way, public transfers might be less effective than they look since they could be "crowding out" private ones.  Private transfers can affect calculations of the distribution of income. Suppose a data set contains a variety of income measures but not private-transfer income. Income disparity measures calculated from the data would be biased. Inequality would be exaggerated, for example, if the omitted private transfers flowed from high to low-income households. Another area where private transfers could figure prominently is that of credit markets. These markets do not work well in many developing countries, partly due to the high cost of obtaining information and trustworthy collateral but also because of government regulation. Private inter-household transfers may act as an informal credit market aimed at overcoming barriers to borrowing. If so, policies designed to increase household access to formal credit markets might prompt reductions in private transfers. Suppose, for example, that government educational loans become available but, as a result, parents decide to reduce their lending to children in school. Private transfers mitigate the policy's impact. Finally, private transfers could facilitate labor mobility and household migration. Policies aimed at helping workers to respond better to economic incentives, say, by e,sing rural-urban migration, could simply prompt reductions in private transfers. C. Motives for Private Transfers The impact of private transfers on the effectiveness of public policy depends on the motives for private transfers. This section explains how. Why do people make transfers? At least two possible reasons exist. The first is altruism. Adult children, for example, might give to their parents because they care about them and get vicarious satisfaction from giving. Modern analysis of altruism's implications were developed by Becker (1974). Many researchers (for example, Adams (1980); Tomes (1981);  Menchik and David (1983)) have uEed Becker's model to analyze bequests in the United States. But the altruism model has received less attention in the development literature. Another conceivable motive for private transfers is self- interested exchange. For example, family members might help with home production or provide other forms of in-kind support in exchange for financial transfers. Such exchange could be contemporaneous or part of a long-term contract. Cash transfers given today might be repaid, in cash or in kind, in future years. Economists have recently begun to apply the exchange idea in a variety of settings, including household production (McElroy and Horney, 1981), private annuity insurance (Kotlikoff and Spivak, 1981) and the exchange of cash for in- kind services (Bernheim, Shleifer and Summers, 1985; Cox, 1987). Exchange behavior is implicit in many of the analyses of family behavior in the development literature. In their survey cf the migrant remittance literature, Rempel and Lobdell (1978) conclude that "Remittances should be seen as reflecting primarily the self-interest of the migrant.n (p.336) They suggest that remittances might aptly be interpreted as repayments for migration assistance or as insurance premiums against income shortfalls. Rosenzweig and Wolpin (1985) explain family-farm dynasties as the outcome of intergenerational contracts that maximize gains from knowledge about farm characteristics. Kaufmann and Lindauer (1986) view private transfers as the outcome of an implicit social insurance contract among a network of related households, with transfers to temporarily disadvantaged households acting as insurance payments. Lucas and Stark (1985) eschew the strict altruism/exchange dichotomy in favor of an eclectic approach that recognizes each motive as "tempered altruism or enlightened self-interest." (p. 901) Family members  - 10 enter into insurance contracts to protect against individual income shortfalls, and mutual altruism helps enforce the contracts. But Cox and Jakubson (1989) show that often, even if transfers are influenced by both motives, in a given instance only one will predominate. The main reason transfer molives are important is that they determine the outcomes of public income redistribution. The altruism model predicts that public transfer programs have little effect on the distribution of economic well-being. With altruism, changes in public transfers are simply offset by corresponding changes in private ones. To see why this occurs, consider the main premise of the altruism model. The donor gives in order to experience indirectly the increased well-being of the recipient. The donor calculates total pre-transfer income and, based on his/her feelings of altruism toward the dependent, determines how much they both will consume by making a private transfer. Now suppose that a public transfer program taxes the donor and gives the proceeds to the dependent. Combined income of the spending-unit (defined as donor plus dependent) has not changed and neither, presumably, has the donor's attitude toward the dependent. So the donor's calculation of optimal consumption for both donor and dependent will not change. The only thing that has changed is individual, pre-private transfer incomes. The donor need not make as large a private transfer to attain desired consumption for the dependent. The impact transfers of the public transfer program is completely offset by changes in private transfers. Of course, not all public transfer programs leave aggregate income of the spending-unit unchanged. Further, a public transfer program might give the dependent more than he or she would have received privately. Also, many households neither give nor receive private transfers and in these instances there are, of course, no private transfers to be displaced  private transfers that occur with altruism. Still, the altruism model predicts that, if altruistic private transfers occur, they diminish the effects of public income redistribution. In an extremely influential article, Barro (1974) uses an altruistic framework to show how private transfers can undo the forced intergenerational transfers associated with deficit spending and Social Security. His analysis predicts that, with operative private transfers, the national debt will not hurt future generations because older ones will leave higher bequests, so that deficits matter little for either generation. A similar argument applies to social security. Public transfers from young to old merely reduce private ones. Again, altruism is necessary for these results. Exchange-motivated transfers can interact with public transfers in an entirely different way. In fact, they can actually exacerbate, rather than offset, the effects of changes in public redistribution on the well- being of private transfer recipients. To illustrate, consider the following contrived but illuminating example. Suppose a donor makes private transfers in exchange for in-kind services rendered to him by the recipient (for example, home production). For every hour of the recipient's work at home, the donor pays the recipient at the hourly market wage rate. Now consider the effects of taxing the donor and subsidizing the recipient's wage. The first order effect of this scheme is the same as with two unrelated individuals: that is, the donor is made worse off and the recipient better off. But a second round effect occurs. The donor must pay higher compensation for the services of the recipient (who, as a result of the subsidy, does not value the donor's help as much as before). This detracts further from the donor's well-being, and adds more to that of the recipient. This  - 12 - "amplification" outcome is exactly the opposite of that predicted by the altruism model. Knowing the motives behind a private transfer is essential for understanding the connection between public and private transfers. The connection is important since nearly all public policies, including those that focus on the economy's general performance, redistribute income from one group to another. A large fiscal deficit, for example, shifts income from future generations to the current one. The motives for private transfers determine the effects of deficits on the relative well-being of generations. D. Empirical Evidence on Private Transfers Empirical patterns for private transfers indicate a variety of functions and effects: they narrow income inequality, function as social insurance, ease borrowing constraints; contribute to human capital investment in schooling and migration; and interact with public transfers. Evidence on transfer motives is mixed. Some patterns indicate altruism, others exchange, and some could be generated by either motive. We assess the evidence in the light of transfer motives. 1. Transfers and Inequalitv Private transfers tend to equalize the distribution of income, especially by boosting the incomes of the poorest households. For example, private transfers increase bottom-quintile incomes of urban households in Kenya by 90 percent (Knowles and Anker, 1981). Private transfers raise the bottom quintile's share of aggregate consumption by 14 percent in Peru (see Chapter 3, below, in this paper). And they have a substantial equalizing effect or incomes in two Mexican villages analyzed by Stark, Taylor and Yitzhaki (1986). Private transfers also lower the variance in log-income in the United States (Cox and Raines, 1985).  - 13 - At face value, the equalizing effect of private transfers suggests altruism, and the pattern of rich giving to poor is certainly consistent with this motive. But a closer look at transfer patterns indicates that altruism may not predominate. In fact, some transfer patterns run counter to altruism, and are more consistent with exchange. There. are two reasons to question the altruistic motive for transfers. First, the pattern of rich giving to poor is also consistent with exchange. Suppose, for example, that financial transfers purchase in- kind services. If the demand for services is income elastic and the supply price of services is inversely related to income, a pattern of rich giving to poor emerges (Cox, 1987). The second reason to question the altruistic motive comes from a closer look at transfer patterns. Higher income households do give more transfers (Johnson and Whitelaw, 1974, Knowles and Anker, 1981 (Kenya); Ravallion and Dedarden, 1988 (rural households in Java); and lower-income households are more likely to receive them (see Chapter 2 for Peru); Cox, 1987 (U.S.)). However, these patterns alone are not a discriminating test for transfer motives, since they are also consistent with exchange. A better test comes from the relationship between the recipient's pre- transfer income and the transfer amounts received. The two theories, altruism and exchange, can part ways when it comes to this relationship. The altruism model predicts that it is always negative. A shortfall in the recipient's resources, for example, always prompts more generous transfers. But the exchange model admits a positive relationship between the two variables. Higher income strengthens the bargaining position of recipients  - 14 - in exchange, so that when their income increases, they -^an get higher transfers. The empirical evidence on this crucial relationship is mixed. Some studies find an inverse relationship between recipient resources and transfer amounts received, such as Lindauer and Kaufmann, 1986 (El Salvador); Kaufmann, 1982 (Philippines), Ravallion and Dearden, 1988 (rural households, Java) and Tomes, 1981 (U.S., bequests). But others find a positive relationship, which contradicts the altruist hypothesis, namely Lucas and Stark, 1985 (Botswana); Cox, 1987 (U.S.); Ravallion and Dearden, 1988 (urban households, Java) and Chapter 2 (Peru). Since the latter findings cast doubt on altruism, they also cast doubt on the Barro-Becker hypothesis that public transfers merely crowd out private ones. 2. Transfers as Social Insurance Private transfers can insure against the illness, disability, unemployment and old-age related reductions in earning potential. This insurance function may be particularly important when publicly provided social security programs are inaccessible, as is the case in many developing countries. What is the evidence? Old age suDport. Although many developing countries have public pensions, most of these apply only to urban workers in the formal sector. So, except for some urbanized countries (mostly Latin American), coverage is limited. And the problem is compounded by underdeveloped financial markets which lower the returns from saving for retirement (World Bank, 1989). Older generations have to rely on the young ior income support. Transfer patterns are consistent with the notion that transfers provide old age support. Over a quarter of private transfers in Kenyan and Peruvian samples were given to parents from children (Knowles and Anker, 1981; Chapter 3, below). Butz and Stan (1982) and Ravallion and Dearden (1988) found significant transfers from young to old in Malaysia and Java  - 15 - respectively. And, in Peru, over a third of the elderly (aged 61 and over) received transfers--more than twice the comparable figure for those aged 41-50 (Chapter 4, below). As earnings decline late in life, the probability of receiving a private transfer dramatically increases. Indeed, some argue that, in developing countries, old age support is the main reason for having children. Nugent's (1985) recent review of the literature on old age support and fertility documents much controversy, but most evidence indicates fertility decisions are at least partly motivated by a desire to insure against the uncertainties associated with old age. And old age support from children includes time-intensive care in addition to money (see Butz and Stan, 1982). These findings support a private-pension transfer motive but they are inconclusive because the patterns could be generated solely by inadequate capital markets. Disability, illness and unemnloyment. Some empirical evidence suggests that private transfers mitigate the effects of being disabled, ill or unerployed. In Peru, households reporting illness four weeks prior to the survey were more likely to receive private transfers. And transfers apparently respond to the availability of publicly-subsidized medical care. In Indonesia, donors assist the sick and those with recent births in rural areas but not in urban ones, where access to public health clinics is greater (Ravallion and Dearden, 1988). High-quality public health coverage also weakens the connection between private transfers and illness in Peru (Chapter 4, below). Despite their greater frequency, transfer amounts targeted to the ill in Peru are lower than those received by their healthy counterparts. Exchange is a possible explanation. Illness would limit the quality of in-  - 16 - kind services household heads provide for others, which would reduce exchange related transfers. Unemployed households have a greater probability of receiving transfers and received greater amounts. In Peru and in Indonesia, being unemployed significantly increases the probability of receiving a transfer, as well as the amount of the transfer (Chapter 3, belos; RavallLon and Dearden 1988). Female-headed households. A consistent pattern across countries is that females or female headed households have a higher probability of obtaining transfers and of receiving larger amounts than their male counterparts (Salvadorean households in Kaufmann and Lindauer 1986; Botswana individuals in Lucas and Stark 1985; Peruvian households in Chapter 3, below; American households in Cox 1987). The effect persists even after holding constant for current income. Why? One reason is purely technical. Females tend to live longer than males and they may get more transfers due to the old age motives already discussed above. Another reason may be that private transfers compensate females for discrimination in the formal labor market. Even though the female effect is strong even with current income held constant, the transfers may reflect past discrimination. Also, if discrimination holds females back from the formal labor market, they may engage in other activities that entail transfers but are, in reality, compensation for services rendered -- such as child rearing or fosterage (Ainsworth 1989). 3. Migration and Education Another connection between private transfers and risk, analyzed extensively by Lucas and Stark (1985), is migration. Households can minimize risk by diversifying their "portfolio" of jobs. A rural family,  - 17 - for example, might send a family member to the urban formal sector to insure against income shortfalls from poor harvests. Lucas and Stark find migrant remittances are targeted to farms with more risky (for example, drought sensitive) assets. Migration does more than mitigate risk, however. Like education and training, it is an investment in human capital. Human capital investment is most profitable when done early, so that enhanced skills can be used over a long time span. But borrowing constraints are likely to be most severe in the early stages of life. Private transfers can facilitate investment in skills by helping overcome such constraints. Empirical transfer patterns support the idea that private transfers are connected to human capital investment. In Peru, for example, the incidence of transfer receipts among the young (aged 15-30) is twice that of the middle-aged (41-50)--28 versus 15 percent (Chapter 4, below). And those with more advanced schooling receive much higher amounts than those with only a primary education. Further, private transfers appear strongly responsive to liquidity constraints. In Peru, transfer incidence mirrors exactly the age earnings profile: the chances of receiving a transfer are lowest when earnings peak. And evidence from the United States supports the idea that transfers are targeted to people who face borrowing constraints (Cox (forthcoming), Cox and Jappelli (1989)). E. Public Policy and Private Transfers The few available studies suggest a strong connection between private and public transfers. Chapter 4 find that private transfers from young to old in Peru would have been 20 percent higher without Social Security pension benefits. Peruvian social security health benefits dampen private transfers as well. Cox and Jakubson (1989), find that private  - 18 - transfeis would have been 14 percent higher in the United States without public income transfer programs. These estimates are lower than the complete "crowding out" predicted by Barro and Becker, but seem large enough to warrant interest among policy makers. They are particularly important for developing countries where tight budgetary constraints and adverse macroeconomic conditions have forced made governments to look for more efficient means of undertaking social programs. Unfortunately, the relationship between public and private transfers in developing countries has received very little attention. It is an important area for future research. F. Conclusions Private transfers in developing countries are widespread and responsive to social and economic conditions, but evidence on their motives is mixed. Economic theory suggests that private transfers should also respond to public policy, and initial empirical work shows that they do. Empirical private transfer patterns, such as the following, indicate that they may be an important component of social and economic policy design: * Private transfers equalize income; * Private transfers are directed toward the poor, the young, the old, women, the infirm, and the unemployed; and * Public tax and subsidy programs can affect private-transfer behavior.  - 19 - The policy implications are important; when private behavior adjusts, there may be unforeseen or unintended implications for public transfer programs, in terms of who benefits and by how much. Additional research is needed to complement and substantiate the few available studies if these private adjustments are to be used to make public policy more effective and efficient.  - 20 - III. WHO GIVES AND WHO GETS PRIVATE INTER-HOUSEHOLD TRANSFERS IN PERU? High quality data on private transfers are scarce. Researchers iust often draw inferences from small samples and idiosyncratic case studies. Even in large surveys, key variables like health status and unemployment are often lacking. And no survey to date has gathered extensive information for both public and private transfers. The World Bank's Peruvian Living Standards Survey (PLSS) remedies many of these deficiencies. The survey covers a large nationwide sample of households. It contains extensive information on the economic situation of survey respondents, permitting the identification of vulnerable groups such as the ill, the unemployed, the under-insured and the poor. So we can measure how much more is given privately to those in economic distress. Also the PLSS contains high-quality consumption data. We can accurately gauge the impact of private transfers on the distribution of economic well- being. This chapter is organized as follows. First, we describe the PLSS. Next we look at the impact of private transfers on the distribution of household consumption, and at the insurance function of transfers. We then explore rural/urban differences in private transfers. Finally, we look at the connection between public and private transfers. Findings from the PLSS indicate that private transfers play a key role in the economic life of households. Transfers follow a pronounced life-cycle pattern and vary according to education. They are targeted toward the ill, the unemployed and women. The most novel finding from the PLSS is that public policy appears to affect private transfer behavior. Transfers vary depending on whether households are covered by Social Security. This finding could have implications for policy design.  - 21 - A. Data PLSS was conducted by the World Bank in conjunction with the Peruvian Instituto Nacional de Estadistica (INE). The PLSS gathered socioeconomic information for a sample of 5,109 housAholds, comprising about 27,000 persons. Field work took place between June 1985 and July 1986. The household is the unit of observation for our analysis. We deleted those with missing data for any of the following: private transfers, age, edutcation of household head, parental schooling, illness, household size, gender of household head, consumption and urban/rural residence. The selection rule reduced the original sample of 5,109 to 4,184. The questions on transfers to other households given are contained in section 11, part E of the PLSS. Respondents were asked: "Has any member of your household sent money or goods--regularly or irregularly--to persons who are not members of your household during the last 3 months?" They reported the recipient's relationship to households head (for example, son, parent) and residence (for example, country-side, city). Respondents reported the value, in intis (in 1986, US$1 = 14 intis), of cash and tn- kind transfers given in the past three months. The same questions were asked for inter-household transfers received (Section 13, Part B). Of the 4,184 households in our sample, 1,216 reported giving a private transfer to another household and 1,144 reported receiving one. Four hundred and forty six reported both giving and receiving. Information on the incidence of private transfers is given below.  - 22 - Percentage of Sample Number (N - 4,184) Households GiAng 1,216 29.06 Households Receiving 1,144 27.34 Households Both Giving and Receiving 446 10.66 Households Neither Giving Nor Receiving 2,270 54.25 Because some households both gave and received, we focus on net receipts (in other words, transfers received minus given) and net donations (transfers given minus received) in what follows. A household is a net transfer recipient if gross transfers exceed those given, and a net transfer donor if the opposite is true. The breakdown of households by net transfer status is given below: Percentage of Sample Number (N - 4,184) Net Transfer Donors 978 23.37 Net Transfer Recipients 905 21.63 Net Transfer Equals Zero ("Others") 2,301 55.00 Because 446 households both gave and received, some givers are "net recipients" and vice versa. For simplicity, we refer to net transfer recipients as "recipients" and net transfer donors as "donors" or "givers." Further, 31 households both gave and received the exact same amount. So the "others" category in the table above contains 2,301 households, even through 2,270 neither gave nor received private transfers. Households reported sources and destinations of transfers by relation. The following is an account of sources of transfers received.  - 23 - Number of Percentage of Percentage of T;ansfers Transfers Intis Transferred 1. Parents 281 24.4 28.0 2. Other Relatives 279 24.3 16.0 3. Children 431 37.5 28.3 4. Son or Daughter-in-Law 26 2.3 5.5 5. Grandchildren 11 1.0 0.5 6. Spouse 38 3.3 7.6 7. Non-relative 84 7.3 14.2 TOTAL 1.150 100.0 lQO.O The majority of transfers flow between parents and children, though other relatives account for a quarter of the total. But the latter give smaller amounts; their share of transfer amounts is 16 percent (Figure 3.1). In- laws, grandchildren, spouses and non-relatives comprise only a small fraction of transfer sources. Since we are looking at inter-household transfers, spouses account for a negligible proportion of transfers. For such a transfer to occur, spouses would have to reside in separate households, which is rare. B. Transfers and the Distribution of Welfare Peruvian patterns corroborate the evidence for other developing countries that private transfers have an equalizing effect on the distribution of economic status and well-being. While household income is commonly used as a welfare indicator, reliable non-wage income was not readily available in the data base. Instead, we follow other analysts who have used consumption, which can be interpreted as a proxy for permanent income. (See Glewwe (1988) and Glewwe and van der Gaag (1988) for a similar justification.)  - 24 - Figure 3. 1 Sourc of Transfers in Peru (Percent) OtftO mastw., (16) _~ _ _ , ., (23) children (26) ..---*4* -.ei.e (76) Som_ _O-S  - 25 - To put the figures in perspective, consider the average transfer amount as a fraction of consumption. The average transfer received, for the entire sample, was 34.48 intis per month, which accounted for 1.6 percent of average monthly consumption. (All inti values in this paper are reported on a monthly basis.) The average transfer among recipients was 159.41 intis, which accounted for 8.5 percent of consumption for the sub- sample. A second way to assess the size of private transfers is to compare them with public transfers from social security. Social security retirement benefits over the three-month period were 17.80 intis. Private transfers are twice as large as Social Security retirement transfers--34.48 versus 17.80. Private transfers have a more pronounced effect on the distribution of economic well-being than social security. Table 3.1 shows how each type of transfer affects the distribution of consumption. The second column shows the distribution with all transfers removed. In other words, this measure is actual consumption minus private and public transfers received, plus private transfers given, plus social security tax payments. Column 3 shows the effects of private transfer receipts and donations on the distribution of consumption. Column 5 of the table shows the effects of public transfers on the distribution; social-security income is added and tax payments subtracted. Column 7 contains the actual distribution of consumption (in other words, with both private and public transfers).  - 26 - Table 3.1. Effeots of Public and Private Transfers on the Distribution of Well-Being Share of Aggregate Consumption (Percentage) (1) (2) (3) (4) (5) (6) (7) (8) After both After Percentage After Percentage Private & Percentage Consumption Before Private Change Public Change Public Change Quintile Transfers Transform from (1) Transfers from (1) Transfers from (1) Lowest 4.085 4.643 (+13.66) 4.241 (+3.82) 4.798 (+17.45) (694 & below) Fourth 8.768 8.875 (+1.22) 8.785 (+0.19) 8.982 (+1.41) (695-1,192) Third 13.814 13.83 (+0.15) 13.839 (0.18) 13.859 (+0.33) (1,193-1,795) Second 21.184 21.075 (-0.51) 21.198 (+0.07) 21.089 (-0.45) (1.176-2,910) Higbhst 52.189 51.610 (-1.12) 51.975 (-0.41) 51.398 (-1.52) (2,911 & above) Before private transfers, the lowest quintile's share of aggregate consumption is 4.085 percent. After private transfers, the share increases to 4.643--a boost of 13.66 percent. In contrast, public transfers alone increase the lowest quintile's share of consumption to only 4.241--an increase of 3.82 percent. The same pattern occurs for the next-to-lowest (fourth) quintile-- private transfers have a greater impact on consumption shares. Public transfers actually raise the second quintile's share a bit, while private transfers reduce it. Private transfers reduce the highest quintile's consumption share more than public ones do. Much of the variation in total consumption can be explained by educational levels. The human capital framework emphasizes the role of education in enhancing income and, thus, consumption. So it is not surprising to find that private transfers vary by educational attainment in a pattern similar to that described above (see the table below and Figure 3.2).  - 27 - Average Percentage Average Amount Among Number Receiving Amount(Intis) Recipients(Intis) No School 674 24.8 15.08 64.50 Initial of Primary 2,067 20.1 19.23 95.53 Secondary 840 23.5 61.27 261.23 Technical 142 18.3 43.70 238.70 Post-Secondary 111 21.6 45.77 211.67 University 350 21.4 88.59 413.43 The incidence of private transfers eoes not follow a distinct pattern across educational categories, but amounts do tend to increase with education. Average transfers for recipients with no schooling are only 64.50 intis; their university educated counterparts get 413.53 intis. Part of the education effect is likely to be due to differences in donor incomes. University graduates are more likely to be linked to high-income donors than are those with only primary schooling. Transfers given are positively related to educational attainment: Average Percentage Average Amount Among Number Giving Amount(Intis) Givers(Intis) No School 675 10.5 14.07 133.57 Initial or Primary 2,067 22.1 28.01 126.69 Secondary 840 28.5 40.69 143.00 Technical 142 33.1 48.83 147.53 Post-Secondary 111 40.5 206.61 509.38 University 350 34.0 75.99 223.52  - 28 - Figure 3.2a [ % of Households Reciving Transfers by Educalion of Household Head NO SChaGI 25 - 0 Smary Ee n 1 Past-Secon 14~~~1 University 0 Educationl Leveo Figure 3.2b Average Amount of Transfers Received by Education of Houshold Head 90l 80X NOs^o 70 50 40 j ~~~0 Post-S.con 20 - W 'versity EdugotIon Le  - 29 - C. Transfers as Social Insurance Private transfers tend to be given to those with fewer economic resources, as indicated below. Average Percentage Average Amount Among Number Receiving Amount(Intis) Recipients(Intis) < Median Consumption 2,092 23.7 17.64 74.38 > Median Consumption 2,092 19.5 51.30 262.53 About 24 percent of households with less than medium consumption received transfers, compared to about 20 percent of those with greater than median consumption. But recipients in the group with higher consumption got bigger amounts--262.53 intis versus 74.38. The economically disadvantaged, measured either by consumption or unemployment, do not give as much as the more fortunate. The patterns are depicted below. Average Percentage Average Amount Among Number Giving Amount(Intis) Recipients(Intis) < Median Consumption 2,092 15.8 16.61 105.23 > Median Consumption 2,092 31.0 58.90 190.26 Unemployed 1,170 15.8 15.20 96.15 Not Unemployed 3,014 26.3 46.52 176.83 Other studies came to the .same conclusion -- that private transfers are targeted towards the poor. In Kenya, urban households in middle income groups gave the largest fractions of their income and the  - 30 - lowest income groups r, eived the most (Knowles and Anker, 1981). In Mexico, remittances from the U.S. have a profound equalizing effect on migrants' home villages, although remittances from internal migrants embody a large returns-to-schooling component (Stark, et. al, 1986). Ravaillon and Dearden (1988) find that transfers reduce income inequality in rural areas (and in urban ones too, but only slightly). Kaufmann and Lindauer (1986) advance a stronger v rsion of the targeting pattern; social networks direct transfer payments to those families with incomes below a "basic needs" level. They conclude that "the performance of the income variables seems to support the view that progressive distributional outccomes are being realized." (p.349) In addition to compensating directly for income, transfers also appear to act as social insurance for unemployment, old age and disability. Age is one of the most important variables affecting transfer receipts. Receipts are highest for the young and the old and least for the middle- aged. Figure 3.3 shows this U-shaped pattern. The figure suggests that private transfers function in part as an informal credit system for households, in other words, a substitute for banks and credit unions. Access to credit markets is limited for many Peruvian households. They probably turn to relatives and friends for funds early in the life-cycle when income is lowest. The high incidence of transfers for older households could be repayments for past loans. Or they could be altruistically motivated transfers, spurred by the desire to boost resources for those whose incomes have fallen.  - 31 - Figure 3.3a | % of Hous u*o c reCin Tranusfes byA of Household Head 4S3 .5 40 ISJ R3re 3. 31-40 30 41-so 25 - 51-60 Is4 61-70 10 7 Age of H4ousehold fta Figure 3.3b Averag Amount of Traaisfer Received oy Age of Hou3shold Hea=d t5-Jo 50 - ~ 40 -~ ~ ~ ~ ~ ~ ~ ~ ~~~~~~14 41-50 30 5i-6 20 61-70 >70 10 0 Age of NouswW meis  - 32 - Average Percentage Average Transfer Receiving Transfer Amount Among Number Transfers Amount(Intis) Recipients(Intis) Age 15-30 443 27.5 53.38 193.82 Age 31-40 936 17.6 21.87 124.06 Age 41-50 926 14.5 19.11 132.08 Age 51-60 727 1S.7 39.64 201.55 Age 61-70 482 30.1 50.88 169.12 Age 70 and over 309 40.5 35.02 86.56 The age pattern for giving is the exact opposite of the one for receipts. Average Percentage Average Transfer Giving Transfer Amount Among Number Transfers Amount(Intis) Donors Age 15-30 443 19.9 19.92 100.28 Age 31-40 936 25.5 29.59 115.90 Age 41-50 926 26.3 38.60 146.51 Age 51-60 727 28.2 56.92 201.87 Age 61-70 482 17.4 58.41 335.15 Age 70 and Over 309 13.3 15.14 114.10 The proportion giving first rises then falls with age. But the average amount for givers, however, steadily rises for all but the highest age category. Ravaillon and Dearden (1988) also find that transfers are targeted to the elderly in rural areas and to both young and old in urban areas of Java, Indonesia These age patterns suggest that transfers smooth consumption for the liquidity-constrained. Behrman and Deolalikar (1987) also find evidence for the income-smoothing hypothesis.  - 33 - Another prominent pattern is differences in receipts by gender; female-headed households receive more. Average Percentage Average Amount Among Number Receiving Amount(Intis) Recipients(Intis) Males 3,618 8.3 26.65 145.56 Females 666 39.2 75.87 193.59 Incidence and size of receipts are higher for female-headed households. There are three possible reasons for this pattern. First, women tend to be poorer so transfers might be compensating for income deficiencies. Second, these transfers might represent payments for in-kind services provided to other households. If women are frequently involved in inter-household services (for example, childeare), they might receive more private transfers. Third, part of the gender effect may reflect male- female differences in life expectancy. A lot of private giving goes to the elderly, and women live longer than men. So private transfers may be given to widows. A much higher proportion of male-headed households give transfers than female-headed ones. Gender differences in giving are summarized below. Average Percentage Average Transfer Giving Transfer Amount Among Number Transfers Amount(Intis) Giving(Intis) Males 3,618 25.2 41.94 166.32 Females 666 13.7 15.74 115.21  * 34 - The average transfer among female givers is also markedly lower than that among males. So the gender pattern for giving is the opposite of that for receipts. The gender differences above are consistent with those found for Botswana (Lucas and Stark, 1985) and El Salvador (Kaufmann and Lindauer, 1986). In those countries, female-headed households have a higher probability of obtaining transfers and they receive larger amounts. Similar evidence has been found for the United States (Cox, 1987). Private transfers appear to respond to economic distress (see below). Average Percentage Average Amount Among Number Receiving Amount(Intis) Recipients(Intis) Ill 2,164 24.4 32.70 33.76 Not Ill 2,020 18.6 36.39 195.50 UnemployedI 1,170 32.6 60.77 186.12 Not Unemployed 3,014 17.4 24.28 139.91 A Er<i-ter percentage of t'hiose reporting illness (of either head or spouse) four weeks prior to the survey received transfers. But the average amount among recipients was higher for those not ill. A greater fraction of households unemployed 12 months prior to the survey received transfers. The average amount for recipients was higher for the unemployed as well. These patterns suggest transfers function in part as private insurance. The proportion of givers does not vary with illness, which is surprising.  - 35 - Average Percentage Average Transfer Giving Transfer Amount Among Number Transfers Amount(Intis) Givers(Intis) Ill 2,164 23.5 36.06 153.60 Not Ill 2,020 23.3 39.60 10.18 Further, amounts given are slightly higher for those not ill. A possible explanation is that those prone to illness, due to, zay, limited access to good water supplies, might form informal pr.ivate insurance schemes with similar households. This behavior would boost the incidence of both donations and receipts among the ill. D. Transfers. Rural/Urban Differences and MiXra_ton Receipts are much higher for urban households than rural ones. The patterns are listed below. Incidence of receipts is higher for urban households as well. Average Percentage Average Amount Among Number Receiving Amount(Intis) Recipients(Intis) Urban 2,241 25.3 57.51 226.89 Rural 1,943 17.3 17.92 45.68 Urban-rural differences in donations mirror those for receipts. Transfers given by urban households were more frequent and larger.  - 36 - Average Transfers Percentage Average Amount Among Number Giving Amount(Intis) Givers(Intis) Urban 2,241 27.0 49.02 181.27 Rural 1,943 19.1 24.79 129.47 Survey respondents reported the sources and destinations of transfers according to place -- countryside, village, town and city. So we can trace urban-rural patterns in transfers. We used the following convention -- the categories "village", "town" and "city" as urban places and "countryside" as rural. The patterns are depicted below. Number of Percentage of Total Percentage of Total Transfers Transfers Amount Transferred Urban to Rural 711 32.54 37.86 Rural to Urban 645 29.52 11.44 Urban to Urban 351 16.06 13.44 Rural to Rural 478 21.88 37.26 TOTAL 2.,185 100.00 100.00 Many transfers cross urban-rural boundaries, but a significant minority (38 percent) occur between households that reside in the same place (see Figure 3.4). What about the evidence in other developing countries? As in Peru, in Indonesia the percent of households receivinlg transfers is higher in urban than in rural areas. But the percentage of households giving is higher in rural areas there. Average receipts are also much higher in urban than in rural areas 'Ravaillon and Dearden 1988). Much of this may be caused by urban-rural income differences.  4- I a C )S t S S c I I I U 0 a G) S 0 I' .1 .4 1 I N U - a a S. S Li U  - 38 - A significant proportion of transfers cross rural-urban boundaries. Part of the pattern is likely to be due to implicit contracts among migrants and stayers. Lucas and Stark (1985) argue that in Botswana, "to allocate certain members as migrants may be a Pareto-superior strategy, and remittances are the mechanism for redistributing the gains." (p. 914) Transfers help spread the risk of migration, and help parents to invest in the education of youngsters, who migrate to town, to reap returns and to repay the initial outlay. Similarly, Knowles and Anker (1981) conclude that, in Kenya, "migrants are under a strong obligation to send transfers back to their home area but that this obligation weakens significantly the longer they reside away." (p. 217) These results corroborate evidence gathered from international remittance behavior in Mexico (see Stark et al. 1986). E. Public and Private Transfers Private transfer patterns differ depending on whether households participate in social security. Two examples are given below. First, consider the sample of urban households aged 60 or over. Average Number Percentage Average Amount Among (Age 60+) Receiving Amount(Intis) Recipients(Intis) Receiving Social Security 112 25.9 84.33 325.69 Not Receiving Social Security 276 40.9 74.09 180.96 A much higher proportion of those without Social Security pensions got private transfers than those with Social Security. A possible reason is that social security "crowds out" private giving. Children whose parents  - 39 - are provided for by public transfers have less incentive to contribute to their well-being. But note also that private transfer recipients who also received social security retirement income also received higher amounts, on average, than their counterparts not receiving social security. A possible explanation is that those in the social security system tend to be high- income households with linkages to high-income children. The social security system provides health insurance coverage in addition to retirement benefits. And private transfers to households that are ill differ depending on social security coverage. This pattern, for the sample of urban households, is depicted below. Average Percentage Average Transfer Receiving Transfer Amount Among Number Transfers Amount(Intis) Recipients(Intis) Ill & Covered by Social Security 457 24.7 50.29 203.40 Ill & Not Covered by Social Security 679 33.3 58.16 174.74 Transfer incidence is higher for urban households with members who are ill but not covered by social security. Apparently, eligibility for public health benefits "crowds out" private giving targeted toward those who are ill. The last two tables suggest an interaction between public and private transfers which we will scrutinize further in later research.  - 40 - F. Conclusions As in many other countries, private inter-household transfers in Peru are pervasive. Forty five percent of households are either donors or recipients. Transfer patterns indicate that they may be important in designing social policy. * Private transfers tend to equalize income. e Aside from the poor, private transfers tend to be directed towards other vulnerable groups such as the young, the old, the infirm and women. * The impact of relevant policy change, such as tax reform, on private transfers should thus be monitored. e Public subsidies may displace private transfer behavior.  - 41 - IV. MOTIVES FOR PRIVATE INTERGENERATIONAL TRANSFERS: AN ANALYTICAL FRAMEWORK AND PRELIMINARY EVIDENCE FROM PERU There are two competing hypotheses that explain transfer giving. One is that households give to satisfy altruistic feelings. The other is that households give because they expect something in exchange. These two motives imply different outcomes for public policies that redist-ibute income. For example, Barro (1974) shows that altruistic households could completely neutralize the forced inter-generational transfer associated with government borrowing by adjusting their own private transfers. Changes in private inter-generational transfers could likewise undo public social security transfers, education gnd health subsidies and other welfare programs if households are altruistic. If households are motivated by exchange, these results do not necessarily hold. Yet rigorous tests of the motives for private transfers are only beginning to be undertaken. This is partly due to a dearth of quality data, even in the U.S. (Cox, 1987). There are almost none in developing countries (see Chapter 2, above, in this paper). This chapter fills this gap with a case study of Peru. One contribution is that it develops a rigorous test based on a model that is particularly apt for developing countries -- that of households that are liquidity constrained. Thus, it adopts an inter-generational approach, presented in Section A, whereby transfer behavior reflects that  - 42 institutional constraint. Another contribution is the use of a detailed data base, described in Section B, that contains information about income, trAnsfers and access to publicly provided services. Such data are uncommon in many countries. Finally, the paper uses the data and the model to conclude that exchange is a stronger motive for giving in Peru than a-truism (Section C). The policy implications of these results are discussed in Section D. A. Theory The relationship between private transfers and income can test the altruism and exchange motives for giving. To show this, we present a model based on utility maximization by households (or heads of households). In order to capture the impact of liquidity constraints on inter-generational transfers, the model is one of overlapping generations and works as follows. The life-cycle of an individual consists of four periods: two "child" periods and two "parent" periods. During the child phase, the individual has a parent but no children. When the individual proceeds from the child phase to the parent phase, the parent dies and a new child is born. The overlapping generations scheme is depicted below, where k and p denote child and parent phases respectively. Periods Generation 1 2 3 4 5 6 7 8 i-l k k p p i k k p p i+l k k p p  - 43 - Since the analysis is aimed at inter vivos transfers, the model will focus solely on transfers that take place when generations overlap. The bequest motive is not operative, where a bequest is defined as a transfer from a parent in generation i to a parent in generation i+l. Conversely, a parent in generation i cannot borrow against the income of a parent from a future generation. Transfers flow only between individuals in overlapping generations. To simplify the analytical results (without losing anything essential), we assume that a child cannot borrow against future income, and that the child would rather borrow than shift own-income from the child to parent phase or from period 1 to 2 during the child phase. The parent has access to capital markets. 1. Altruism With these assumptions, the scheme can be reduced to a simple two- period model with a family comprised of two individuals, the parent and the child. Transfers take place when generations overlap. We now consider the transfer under two alternative assumptions: altruism and exchange. With altruism, the parent cares about the child's well-being. The parent's objective function is: U - U1(Cpl, Vl(Ckl)) + U2(Cp2, V2(Ck2)) (4.1) (1 + p) where Ui - parent's level of well-being in period i, i - 1,2, Cpi -parent's consumption in period i Vi - child's level of well-being in period i, Cki - child's consumption in period i, and p - the rubjective rate of time discount.  - 44 - The function U is assumed to be increasing and concave in each of Lts arguments, and the subjective rate of discount is equal for parent and child. The objective function is maximized subject to the following constraints: Cpj + 0p2 + T + T2 Epl + Ep2 (4.2) (l+r) (l+r) (l+r) Ckl - Ekl + Tl, (4.3a) and Ck2 - Ek2 + T2 (4.3b) where Epi - parent's earnings in period i, Ei child's earnings in period i, Ti = transfers made from parent to child in period i, and r the market rate of interest. The nature of constraints (4.2) and (4.3a-b) is such that the parent has access to capital markets but the child does not. The child cannot borrow in the market and must consume out of current earnings and transfers. We now solve for an interior solution for transfers. Define the individual's "endowment" marginal utility of consLuption as the marginal utility of consumption when no transfers take place. In symbols let us denote this endowment marginal utility as [(UJ]I i = 1,2, j = p,k. A transfer from parent to child in period i will take place if fui 1< [aui , LaCpi J aCki  - 45 - and write an expression for the latent variable that detetmines the transfer de-'.sion as: t _(8Ui 0o (J 1JUi (4.4) and Ti > 1 iff ti > 0, Ti - 0 otherwise. Diminishing marginal utility implies that: at1 < 0 i - 1,2 ati > O i ' f 8Ekf aEkf and at_ < 0 i - 1,2, f 1,2. aEpf The latent variable t* is inversely related to the child's contemporaneous earnings and positively related to his earnings in other periods. A rise in contemporaneous income eases the child's liquidity constraint in the current period, reducing t*. A rise in child's earnings in a period other than the current period will raise his optimal consumption profile. With current earnings held constant, this implies a * rise in t . Finally, a rise in parental earnings, Epi, i - 1,2, increases the child's optimal consumption and, therefore, t*. The comparative statics results for transfer levels, Ti, follow precisely the same pattern as those for t* Given an interior solution for private transfers, the child pursues a non-liquidity constrained consumption path. Operative transfers imply that the time path for child consumption is determined by the following Euler equation:  - 46 - 8Vk _ (l+r) BVk (4*5) aCkl (l+p) 8Ck2 This is precisely the equation that would have detarmined consumption had the child not been liquidity constrained. 2. Exchange Through Inter-generational Loans In this model, family members make transfers that arise out of bargaining over the terms of an inter-generational loan. As before, the child is liquidity constrained in the first two periods, but each family member cares only about his own consumption. Though family members are selfish, they honor their commitments. In particular, the child will repay loans from the parent. The parent knows this but the bank does not. This situation corresponds to the informational linkage that leads to the constraint. We also assume that the child cannot make borrowing arrangements with anyone else; the parent is the only source of funds. This assumption is not necessary but simplifies the exposition. Finally, the child is willing to borrow at rates higher than the market rate of interest. The parent, therefore, has an incentive to lend to the child because he can earn an above market rate of return on his saving. For simplicity, loan repayments take the form of monetary payments. Inter-generational lending is a bilateral monopoly problem. The terms of the loan are determined by selfish bargaining. Let us first assume that the parent dominates the bargaining arrangement. Other bargaining frameworks are considered L1ter. Since the parent dominates the bargaining, the child receives his "threat-point" utility, defined as the utility the child would obtain if he  - 47 - walked out on the game and pursued a liquidity constrained consumption path. The child's utility function is: Vk - Vl(Ckl) + V2(Ck2) _ Vl(Ekl) + T + V2(Ek2-R) (4.6) (1 + p) (I + p) where T denotes parental loans and R denotes repayments. The function V is increasing and concave in each argument. The child threat-point utility level is 0 0 V2(Ek2) (4.7) Vk m V 1(Ekl) + 2k)(47 (1 + p) The parent's problem is to maximize the gains from lending, - T + R (1 + r) subject to the constraint that the child remains in the game, in other 0 terms, Vk - Vk- The first issue is the existence of an interior solution for transfers. Define the child's marginal utility of consumption at the endowment point (where transfers equal zero) as OVk i - 1,2. The parent's 8Eki gains from trade exist if OVk > (1 + r) OVk Define the latent aEkl (l + p) aVk2 variables t_aVk. (1 + r) aVk (4.8) aEkl (1 + p) dEk2 and T, R > O iff t > O T - R - 0 otherwise. From the concavity of the utility function, at < 0, at > 0. The aEkl 8Ek2 latent variable that determines the occurrenc^- of a transfer is inversely  - 48 - related to contemporaneous child earnings and positively related to future child earnings. These results are the same as those of the altruism model but the reason is different. Here, transfers take place if the child' s demand price for a consumption loan is greater than the market rate of interest. A fall in first period earnings or a rise in second period earnings will increase the demand price. Three results for the latent variable differ from the altL Asm model. First unlike ti, the variable t is not indexed by time. If t > 0, both transfers and repayments occur. Second, t does not depend on parent earnings. The transfer decision is determined solely by the relationship between the child's demand price for a loan and the market rate of interest. The latent variable would be influenced by parental earnings, however, given a connection between parental earnings and the interest rate faced by him. Finally, given an Lnterior solution, the first period transfer, T1, need not be inversely related to Ekl. An increase in Ekl raises the child's threat-point, making borrowing terms more favorable. This can result in a positive relationship between current earnings and transfers. Given that lending takes place, the time path of child consumption is determined by the relationship between the subjective rate of time preference and the market rate of interest, so that: aVk _ (1 + r) aVk aCkl (1 + p) aCk2 This is identical to expression (4.6) above. Despite the difference in transfer motives, both altruism and selfish bargaining imply that child consumption is determined by the Euler equation when inter vivos transfers are operative.  - 49 - The parent-dominates ascumption is extreme. It implies that the child is no better off in the loan relationship than on his own. The more realistic (but also more cumbersome) Nash solution to the bargaining problem involves choosing T and R to maximize the Nash product: 0 0 N - (Vk - Vk) (Up - Up) (4.9) 0 - Vl(Ekl + T) + V2(Ek2 - R) EV1 (E) -) (1 + P) (1 + P) x I U (W - T + R - U